Detection of epileptiform activity

Abstract

The invention relates to detection of epileptiform activity. In order to accomplish a mechanism with improved specificity to epileptiform activity and with the capability to detect specific type of epileptic patterns, brain wave signal data obtained from a subject is decomposed into at least one predetermined subband, each subband being indicative of a specific type of epileptiform activity. The subband-specific output data obtained represents a time series of a quantitative characteristic of the brain wave signal data. At least one measure is determined for any one or more of the at least one predetermined subband, the at least one measure belonging to a measure set comprising a first measure indicative of the entropy of the subband-specific output data and a second measure indicative of a normalized form of k:th order central moment of the subband-specific output data, where k is an integer higher than three. The presence of a specific type of epileptiform activity may be detected based on the at least one measure of the respective subband.

What is claimed is: 
     
       1. A method for detecting epileptiform activity with an epileptiform activity analysis apparatus, the epileptiform activity analysis apparatus including brain wave measurement sensors, an amplifier stage, an A/D converter, a control unit and a monitor screen, the control unit including a microprocessor, memory, a subband-specific transfer means and a calculating means, the method comprising:
 obtaining brain wave signal data from sensors applied to a subject, and transmitting the brain wave signal data from the brain wave measurement sensors to the amplifier stage; 
 amplifying the brain wave signal data using the amplifier stage to form amplified brain wave signal data; 
 transmitting the amplified brain wave signal data from the amplifier stage to the A/D converter; 
 converting the amplified brain wave signal data using the A/D converter to digitized amplified brain wave signal data; 
 transmitting the digitized amplified brain wave signal data from the A/D converter to the control unit; 
 decomposing, using the subband-specific transfer means, the digitized amplified brain wave signal data into at least one predetermined subband, wherein each subband includes at least one waveform indicative of a specific type of epileptiform activity, and to provide subband-specific time-series data for each of the at least one predetermined subband; 
 determining, using the calculating means, at least one measure for each of the at least one predetermined subband, the at least one measure belonging to a measure set comprising a first measure indicative of the entropy of the subband-specific time-series data of the respective subband and a second measure indicative of a normalized form of k:th order central moment of the subband-specific time-series data of the respective subband, where k is an integer higher than three; 
 indicating the presence of a specific type of epileptiform activity in the brain wave signal data based on the at least one measure of the respective subband regardless of the subject's level of consciousness; and 
 displaying on the monitor screen the presence of the specific type of epileptiform activity in the brain wave signal data of the subject in order to monitor for possible epileptic symptoms. 
 
     
     
       2. A method according to  claim 1 , wherein the brain wave signal data is selected from a group including electroencephalogram (EEG) signal data and magnetoencephalogram (MEG) signal data. 
     
     
       3. A method according to  claim 1 , wherein the decomposing includes employing at least one filter to obtain the subband-specific time-series output data. 
     
     
       4. A method according to  claim 3 , wherein the at least one filter is configured to perform a wavelet transform. 
     
     
       5. A method according to  claim 4 , wherein the wavelet transform is a discrete wavelet transform. 
     
     
       6. A method according to  claim 4 , wherein the wavelet transform has a basis function from a group of Daubechies wavelets or from a group of Symlet wavelets. 
     
     
       7. A method according to  claim 1 , wherein at least one of the at least one predetermined subband is indicative of epileptiform spikes or of phasic waveforms. 
     
     
       8. A method according to  claim 1 , wherein the determining includes determining one measure for each predetermined subband. 
     
     
       9. A method according to  claim 1 , wherein the indicating includes comparing the at least one measure of each predetermined subband with a respective threshold value, whereby a comparison result is obtained for each predetermined sub-band; and
 deciding on the presence of a specific epileptiform activity in the brain wave signal data based on the comparison result of the respective subband, thereby to obtain presence information. 
 
     
     
       10. The method according to  claim 1 , wherein the second measure is indicative of normalized form of k:th order central moment m k  of the subband-specific time-series data, where m k =E[(X−μ) K ]/(E[(X−μ) 2 ]) k/2 , where μ is a mean of a sample set x of the subbband-specific time-series data, and E represents an expected value, and k is an integer higher than four. 
     
     
       11. An apparatus for detecting epileptiform activity, the apparatus comprising:
 measurement means for obtaining brain wave signal data from a subject; 
 subband-specific transform means configured to decompose the brain wave signal data into at least one predetermined subband, each subband being indicative of a specific type of epileptiform activity and to provide subband-specific time-series data for each of the at least one predetermined subband; 
 calculation means for determining at least one measure for each of the at least one predetermined subband, the at least one measure belonging to a measure set comprising a first measure indicative of the entropy of the subband-specific time-series data of the respective subband and a second measure indicative of a normalized form of k:th order central moment of the subband-specific time-series data of the respective subband, where k is an integer higher than three; and 
 indicator means for indicating the presence the specific type of epileptiform activity in the brain wave signal data of the subject in order to monitor for possible epileptic symptoms based on the at least one measure of the respective subband regardless of the subject's level of consciousness. 
 
     
     
       12. An apparatus according to  claim 11 , wherein the measurement means are configured to provide the brain wave signal data from a group including electroencephalogram (EEG) signal data and magnetoencephalogram (MEG) signal data. 
     
     
       13. An apparatus according to  claim 11 , wherein the subband-specific transform means comprise at least one filter. 
     
     
       14. An apparatus according to  claim 13 , wherein the at least one filter is configured to perform a wavelet transform. 
     
     
       15. An apparatus according to  claim 14 , wherein the at least one filter is configured to perform a discrete wavelet transform. 
     
     
       16. An apparatus according to  claim 14 , wherein the at least one filter is configured to perform a wavelet transform having a basis function from a group of Daubechies wavelets or from a group of Symlet wavelets. 
     
     
       17. An apparatus according to  claim 11 , wherein at least one of the at least one predetermined subband is indicative of epileptiform spikes or of phasic waveforms. 
     
     
       18. An apparatus according to  claim 11 , wherein the calculation means is configured to determine one measure for each predetermined subband. 
     
     
       19. An apparatus according to  claim 11 , wherein the indicator means is configured to
 compare the at least one measure of each predetermined subband with a respective threshold value, thereby to obtain a comparison result for each predetermined sub-band; 
 decide on the presence of a specific epileptiform activity in the brain wave signal data based on the comparison result of the respective subband, thereby to obtain presence information; and 
 present the presence information to a user. 
 
     
     
       20. An apparatus according to  claim 11 , wherein the indicator means is configured to present the at least one measure to a user. 
     
     
       21. An apparatus according to  claim 11 , wherein the second measure is indicative of the kurtosis of the wavelet coefficients of the respective subband. 
     
     
       22. The apparatus according to  claim 11  wherein the second measure is indicative of a normalized form of k:th order central moment m k  of the subband-specific time-series data, where k is an integer higher than three, and where m k =E[(X−μ) k ]/(E[(x−μ) 2 ]) k/2 , where μ is a mean of a sample set x of the subband-specific time-series data, and E represents an expected value. 
     
     
       23. An apparatus for detecting epileptiform activity, the apparatus comprising:
 a measurement module configured to obtain brain wave signal data from a subject; 
 a subband-specific transform module configured to decompose the brain wave signal data into at least one predetermined subband, each subband being indicative of a specific type of epileptiform activity and the subband-specific transform module being configured to provide subband-specific time-series data for each of the at least one predetermined subband, 
 a calculation module configured to determine at least one measure for each of the at least one predetermined subband, the at least one measure belonging to a measure set comprising a first measure indicative of the entropy of the subband-specific time-series data of the respective subband and a second measure indicative of a normalized form of k:th order central moment of the subband-specific time-series data of the respective subband, where k is an integer higher than three; and 
 an indicator module configured to indicate the presence of the specific type of epileptiform activity in the brain wave signal data of the subject in order to monitor for possible epileptic symptoms based on the at least one measure of the respective subband regardless of the subject's level of consciousness. 
 
     
     
       24. An apparatus according to  claim 23 , wherein the subband-specific transform module comprises at least one filter. 
     
     
       25. An apparatus according to  claim 24 , wherein the at least one filter is configured to perform a wavelet transform.